For this last component of your Readiness Assessment, you will complete a brief map assignment This is designed to give you practice in creating a visual representation, with converting it to a PNG or JPEG, and uploading it into an assignment window in Blackboard Note that only PNG or JPEG formats are acceptable for map assignments The data for which you are creating a map is a ratio of the the number of legally registered marijuana producers in the State of Washington, by county (Washington has 39 counties), to the number of legally registered marijuana retailers I found these data (Links to an external site ) and then created the Excel sheet On the attached Excel sheet, the data that you will be mapping are found in Column D, titled P to R Ratio Also attached are two different blank maps, by county, of the State of Washington You may use one of these or another that you find elsewhere Your job for this map assignment is to create a choropleth map of the P to R Ratio A choropleth map is a shaded map you need to think about how to best create categories (officially called classifications ) for the data, to determine which counties fall into which category, and then to shade the corresponding counties differently For this introductory assignment, I will ask you to use five categories classifications, but how do you decide where the category boundaries are Here are three common ways Equal Interval Classification This would suggest to us that each category in the legend should be 3 units wide (e g , 0 0 2 8 2 9 5 6 5 7 8 5 etc or 0 0 2 9 3 0 5 9 etc ) Quantile classification This would suggest to us that each category in the legend should have 8 counties in it the breaks between the ranges in each category are dependent upon each category containing 8 counties For example, the 8 counties with the lowest value would be their own category then, the 8 counties with the next lowest values would be their own category and so on Natural Breaks classification In examining the data from highest to lowest, it may be effective to create five categories classifications based on where the data have naturally occurring gaps For example, when I sort the data from highest to lowest, I could argue that a natural break occurs between the P to R Ratio values of 9 0 and 7 70, so the four counties whose P to R ratio value is 9 0 or greater would be in their own category classification After you have decided how to categorize classify the data, and have determined which counties belong to which classification, consider what colors to use for each one You may accomplish this by hand with colored pencils, or with any program that you are experienced in (QGIS, ArcMap, Microsoft Paint, to name a few) Your completed map will also include a title , and a created legend showing the classifications Please visit the GIS Lounge (Links to an external site ) to learn more about what elements are on a map Once your map is completed, take a picture of it (or a scan or a screenshot of it), or save it as a JPEG or PNG via another manner Then, click on the heading for this assignment, scroll down to Assignment Files , and attach it When you are finished and want to send it over to us for grading, click the Submit button in the lower right corner This JPEG or PNG is due by 10a on Tuesday, January 19 Here is an example of a choropleth map for another phenomenon (but still for the State of Washington by county) Rising Education Levels in Washington State In 1990, there were 3 counties in which over 25 of the population had a bachelor's degree or more In 2008 2012, there were 11 Percent of the population with a bachelor's degree or more 10 15 , 15 20 20 25 , 25 30 , 35 40 , 40 45 Data from the US census 25 Rising Education Levels in Washington State In 1990, there were 3 counties in which over 25 of the population had a bachelor's degree or more In 2008 2012, there were 11 Percent of the population with a bachelor's degree or more 10 15 , 15 20 20 25 , 25 30 , 35 40 , 40 45 Data from the US census 25

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For this last component of your Readiness Assessment, you will complete a brief map assignment. This is designed to give you practice in creating a

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For this last component of your Readiness Assessment, you will complete a brief map assignment. This is designed to give you practice in creating a visual representation, with converting it to a PNG or JPEG, and uploading it into an assignment window in Blackboard. Note that only PNG or JPEG formats are acceptable for map assignments.

The data for which you are creating a map is a ratio of the the number of legally registered marijuana producers in the State of Washington, by county (Washington has 39 counties), to the number of legally registered marijuana retailers. I found these data (Links to an external site.) and then created the Excel sheet. On the attached Excel sheet, the data that you will be mapping are found in Column D, titled P to R Ratio. Also attached are two different blank maps, by county, of the State of Washington. You may use one of these or another that you find elsewhere.

Your job for this map assignment is to create a choropleth map of the "P to R Ratio". A choropleth map is a shaded map; you need to think about how to best create categories (officially called classifications) for the data, to determine which counties fall into which category, and then to shade the corresponding counties differently.

For this introductory assignment, I will ask you to use five categories / classifications, but how do you decide where the category boundaries are? Here are three common ways:

Equal Interval Classification: This would suggest to us that each category in the legend should be 3 units wide (e.g., 0.0 - 2.8; 2.9 - 5.6; 5.7 - 8.5; etc.; or 0.0 - 2.9; 3.0 - 5.9; etc.).
Quantile classification: This would suggest to us that each category in the legend should have 8 counties in it; the breaks between the ranges in each category are dependent upon each category containing 8 counties. For example, the 8 counties with the lowest value would be their own category; then, the 8 counties with the next-lowest values would be their own category; and so on.
Natural Breaks classification: In examining the data from highest to lowest, it may be effective to create five categories / classifications based on where the data have naturally-occurring gaps. For example, when I sort the data from highest to lowest, I could argue that a natural break occurs between the P to R Ratiovalues of 9.0 and 7.70, so the four counties whose P to R ratio value is 9.0 or greater would be in their own category / classification.

After you have decided how to categorize / classify the data, and have determined which counties belong to which classification, consider what colors to use for each one. You may accomplish this by hand with colored pencils, or with any program that you are experienced in (QGIS, ArcMap, Microsoft Paint, to name a few).

Your completed map will also include a title, and a created legend showing the classifications. Please visit the GIS Lounge (Links to an external site.) to learn more about what elements are on a map.

Once your map is completed, take a picture of it (or a scan or a screenshot of it), or save it as a JPEG or PNG via another manner. Then, click on the heading for this assignment, scroll down to Assignment Files, and attach it. When you are finished and want to send it over to us for grading, click the Submit button in the lower right corner. This JPEG or PNG is due by 10a on Tuesday, January 19.

Here is an example of a choropleth map for another phenomenon (but still for the State of Washington by county).

Rising Education Levels in Washington State In 1990, there were 3 counties in which over 25% of the population had a bachelor's degree or more. In 2008-2012, there were 11. Percent of the population with a bachelor's degree or more 10-15%, 15-20% 20-25%, 25-30%, 35-40%, 40-45% Data from the US census 25% Rising Education Levels in Washington State In 1990, there were 3 counties in which over 25% of the population had a bachelor's degree or more. In 2008-2012, there were 11. Percent of the population with a bachelor's degree or more 10-15%, 15-20% 20-25%, 25-30%, 35-40%, 40-45% Data from the US census 25%